메뉴
Antibody design using IgGM model. Use this skill when: (1) Epitope-conditioned de novo antibody design, (2) Antibody affinity maturation, (3) Using antigen PDB structure and epitope information. For binding affinity evaluation, use prodigy.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Find the most suitable skill for a given biomedical task. Use this skill when: (1) You are unsure which skill to use for a specific biomedical task, (2) You want to discover available skills for a particular domain, (3) You need to compare multiple skills for a given use case.
Generate diverse druggable molecules for a given target or disease using OpenBioMed's AI-powered drug discovery tools. Use this skill when: (1) Generating drug candidates, molecules, or compounds for a target/disease, (2) Performing structure-based drug design or de novo drug design, (3) Finding or creating molecules that bind to a specific protein target, (4) Discovering potential drugs for a disease name, (5) Designing molecules with specific properties (LogP, QED, docking scores). The skill handles target identification, structure retrieval, molecule generation, and in silico evaluation.
Analyze potential drug-drug interactions (DDI) for up to 5 drugs using KEGG DDI database. Use this skill when: (1) Checking interactions between multiple medications, (2) Assessing DDI risk for drug combinations, (3) Understanding interaction mechanisms and severity, (4) Analyzing CYP enzyme involvement in DDIs.
Generate comprehensive drug development progress reports for disease therapeutic targets. Use when user asks about target drug pipeline, clinical trials, or research progress. Triggers on phrases like "target report", "drug development progress", "clinical trial summary", "靶点报告", "药物研发进展", "竞品分析", "专利分析".
Create new biomedical skills or improve existing ones for the OpenBioMed toolkit. Use this skill when: (1) Creating a new skill from scratch, (2) Capturing a workflow as a reusable skill, (3) Automating a biomedical task, (4) Improving an existing skill. This skill guides through an interactive process: define intent → design workflow → validate with real data → iterate → evaluate.
Query ChEMBL database for bioactivity data on drug-like compounds. Use this skill when: (1) Finding compounds active against a protein target (target-based search), (2) Getting bioactivity profile for a molecule (molecule-based search), (3) Finding drugs for a disease indication (indication-based search).
| name | antibody-design-iggm |
| description | Antibody design using IgGM model. Use this skill when: (1) Epitope-conditioned de novo antibody design, (2) Antibody affinity maturation, (3) Using antigen PDB structure and epitope information. For binding affinity evaluation, use prodigy. |
| license | MIT |
| category | design-tools |
| tags | ["structure-design","sequence-design","antibody","nanobody"] |
| Requirement | Minimum | Recommended |
|---|---|---|
| Python | 3.10+ | 3.10 |
| CUDA | 11.7+ | 11.8 |
| GPU VRAM | 24GB | 80GB (A800) |
| RAM | 32GB | 64GB |
git clone https://github.com/TencentAI4S/IgGM.git
cd IgGM
pip install torch==2.0.1 --index-url https://download.pytorch.org/whl/cu118
pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.1+cu118.html
pip install tqdm requests numpy==1.23.5 termcolor==2.4.0 biopython==1.79 openmm==8.2 pdbfixer ml-collections==0.1.1
python design.py --fasta complex_sequence.fasta --antigen complex_structure.pdb --cal_epitope
# --antigen: the structure of a known complex
# --fasta: the sequence of a known complex
python design.py --fasta design_requirement.fasta --antigen antigen_structure.pdb --epitope 7 8 9 10 11 --output output_dir
# --fasta: Directory path to input design requirement FASTA files, X for design region
# --antigen: Directory path to input antigen PDB files
# --epitope: epitope residues in antigen chain A , for example: 7 8 9 10 11
# --output: Directory path to output PDB files
python design.py --fasta design_requirement.fasta --antigen antigen_structure.pdb --fasta_origin original_antibody_sequence.fasta --run_task affinity_maturation --num_samples 10 --output output_dir
# --fasta: Directory path to input design requirement FASTA files, X for design region
# --antigen: Directory path to input antigen PDB files
# --fasta_origin: Directory path to original antibody FASTA files for affinity maturation
# --num_samples: number of samples for residue
# --output: Directory path to output PDB files
>H # Heavy chain ID
VQLVESGGGLVQPGGSLRLSCAASXXXXXXXYMNWVRQAPGKGLEWVSVVXXXXXTFYTDSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCARXXXXXXXXXXXXXXWGQGTMVTVSS
>L # Light chain ID
DIQMTQSPSSLSASVGDRVSITCXXXXXXXXXXXWYQQKPGKAPKLLISXXXXXXXGVPSRFSGSGSGTDFTLTITSLQPEDFATYYCXXXXXXXXXXXFGGGTKVEIK
>A # Antigen ID, needs to be consistent with the pdb file
NLCPFDEVFNATRFASVYAWNRKRISNCVADYSVLYNFAPFFAFKCYGVSPTKLNDLCFTNVYADSFVIRGNEVSQIAPGQTGNIADYNYKLPDDFTGCVIAWNSNKLDSKVGGNYNYRYRLFRKSNLKPFERDISTEIYQAGNKPCNGVAGVNCYFPLQSYGFRPTYGVGHQPYRVVVLSFELLHAPATVCGP
output_dir/
├── antibody_0.fasta # designed antibody sequence (fasta file)
├── antibody_0.pdb # designed antigen-antibody complex structure (pdb file)
├── antibody_1.fasta
├── antibody_1.pdb
└── ...
Should I use IgGM?
│
└─ What type of design?
├─ Antibody de novo design → IgGM ✓
├─ Nanobody de novo design → IgGM ✓
└─ Binder design for general protein binder → boltzgen
Next: Evaluate binding affinity with prodigy.